To set values for \(\mu _{\alpha _0}, \Sigma _{\alpha _0}\) , we follow the procedure described in [1]}. We do the following: 1) conduct GEE regression analyses using all participant's data in ROBAS 2 in order to assess the significance of each feature; 2a) for features that are significant in the GEE analysis, the prior mean is set to be the point estimate found from GEE analysis and the prior standard deviation is set to be the standard deviation across user models from GEE analysis; 2b) for features that are not significant, the prior mean is 0 and we shrink the standard deviation by half. For feature 3. Exponential Average of Brushing Over Past 7 Days, we imputed that value with the average of past brushing obtained so far for the first week. Recall that ROBAS 2 had no data under \(A_{i, t} = 1\) , so for feature 4. Exponential Average of Messages Sent Over Past 7 Days, we set the prior mean to 0 and set the standard deviation to the average prior SD of the other features. Notice that \(\Sigma _{\alpha _0}\)  is a diagonal matrix where the diagonal values are the prior variances described above.
